Detection of bed position for automation of patient‐monitoring function. Issue 11 (17th September 2018) - Inoue, Madoka; Yasui, Toshiyuki; Taguchi, Ryo; Umezaki, Taizo
Abstract: In hospitals, in order to prevent a patient from falling and fall accidents, there is an increasing demand to detect a lifting movement and a leaving‐off movement of a patient with a camera installed in a hospital room. As a measure for efficiently detecting these operations, a process of specifying a bed position which is an occurrence position of an action is effective. We propose a method to detect bed position from image of monocular camera, using image features and framework of machine learning. By generating a viewpoint conversion image for an input image, a uniform bed shape is acquired even for images at different camera positions. Evaluation was made with 2160 still images and 3888 scene moving images to confirm the usefulness of the method.